| Autor: |
Vikram Puri, Sudan Jha, Raghvendra Kumar, Ishaani Priyadarshini, Le Hoang Son, Mohamed Abdel-Basset, Mohamed Elhoseny, Hoang Viet Long |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 7, Pp 111181-111191 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2019.2934228 |
| Popis: |
The world is consuming large amounts of energy in various forms like electric energy and mechanical energy. Since the electrical energy is an important factor for the development of the world, many researchers tried to generate electricity from renewable energy sources collected by sensors in order to overcome the shortage of electrical energy for household appliances and industrial areas. In this paper, we develop Internet-of-Things (IoT) based system to generate electrical energy from multiple sensors for household appliances and industrial areas. Different sensors namely piezoelectric sensor, body heat to electric converter and solar panel are utilized and connected to the power storage circuit for generation of electrical energy. Two different Artificial Intelligence (AI) models such as Artificial Neural Network (ANN), Adaptive Network based Fuzzy Inference System (ANFIS) are utilized for the total power generated from renewable energy resources. Validation is done through the statistical parameters such as Root Mean Square Error (RMSE) and R2 coefficient of correlation. Result outcome from the models shows that ANN performance is better than ANFIS. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
